Prediction of postoperative pulmonary complications using preoperative controlling nutritional status (CONUT) score in patients with resectable non-small cell lung cancer
- 저자
- Sang Chul Lee
; Jin Gu Lee
; Sang Hoon Lee
; Eun Young Kim
; Joon Chang
; Dae Joon Kim
; Hyo Chae Paik
; Kyung Young Chung
; Ji Ye Jung
- 키워드 (영문)
- underweight; receiver operating characteristic; odds ratio; multivariate analysis; mortality rate; medicine; lung cancer; internal medicine; incidence (epidemiology); gastroenterology; confidence interval; hazard ratio
- 발행연도
- 2020-07
- 발행기관
- Springer
- 유형
- Article
- 초록
- Postoperative pulmonary complications (PPCs) significantly impact surgical outcome. We investigated the predictive ability of controlling nutritional status (CONUT) for PPC after lung resection in patients with non-small cell lung cancer (NSCLC). We retrospectively reviewed data of 922 patients with NSCLC who underwent complete resection from January 2016–December 2017. We analyzed the frequency and characteristics of PPCs and compared receiver operating characteristic (ROC) curves of various prognostic models to predict PPCs. A CONUT score higher than 1 was considered as a high CONUT score. Total incidence of PPCs was 8.6% (n = 79). The proportion of pneumonia was significantly larger in the high CONUT group (P < 0.05). The CONUT consistently had a higher area under curve (AUC) value (0.64) than other prognostic models (prognostic nutritional index (PNI): AUC = 0.61, Glasgow prognostic score (GPS): AUC = 0.57, and assessment of respiratory risk in surgical patients in Catalonia (ARISCAT): AUC = 0.54). Multivariate analysis identified underweight [Odds ratio (OR) = 4.57, P = 0.002] and high CONUT score (OR = 1.91, P = 0.009) as independent PPCs prognostic factors. One-year mortality rate for high CONUT score was significantly higher (hazard ratio = 7.97; 95% confidence interval, 1.78–35.59). Preoperative CONUT score is an independent predictor of PPCs and 1-year mortality in patients with resectable NSCLC.
- 저널명
- Scientific reports
- 저널정보
- (2020-07). Scientific reports, Vol.10(1), 12385–12385
- ISSN
- 0068-1261
- EISSN
- 2045-2322
- DOI
- 10.1038/s41598-020-68929-9
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